With the development of computer technologies, voice recognition technologies have been applied in more and more areas, such as smart home, industrial control, and voice interaction systems of terminal devices. Information can be processed and acquired more conveniently with the voice recognition technologies, thereby improving working efficiency of users.
However, existing voice recognition methods usually include inputting a voice signal to be recognized into an acoustic model obtained by training a pure voice signal, to obtain a voice recognition result. Since the voice signal to be recognized usually differ significantly from the pure voice signal, such voice recognition methods have the problem of low recognition success rate.